Spatially explicit fisheries simulation models for policy evaluation

Abstract

Introduction 308Review of existing models and simulation tools 309Population and ecosystem modelling 309Non-spatial models and the efficacy of no-take zones 309 Metapopulation models 310Spatially explicit demographic models 312Multispecific and ecosystem approaches 318Modelling exploitation and management policies 320Dynamics of the spatial allocation of fishing effort 320 Mixed fisheries 321Bioeconomic modelling 323Policy modelling and fishers' response to management 323A generic simulation tool for policy evaluation 325Spatial and seasonal scales in the model 325 AbstractThis paper deals with the design of modelling tools suitable for investigating the consequences of alternative policies on the dynamics of resources and fisheries, such as the evaluation of marine protected areas (MPA). We first review the numerous models that have been developed for this purpose, and compare them from several standpoints: population modelling, exploitation modelling and management measure modelling. We then present a generic fisheries simulation model, Integration of Spatial Information for FISHeries simulation (ISIS-Fish). This spatially explicit model allows quantitative policy screening for fisheries with mixed-species harvests. It may be used to investigate the effects of combined management scenarios including a variety of policies: total allowable catch (TAC), licenses, gear restrictions, MPA, etc. Fisher's response to management may be accounted for by means of decision rules conditioned on population and exploitation parameters. An application to a simple example illustrates the relevance of this kind of tool for policy screening, particularly in the case of mixed fisheries. Finally, the reviewed models and ISIS-Fish are discussed and confronted in the light of the underlying assumptions and model objectives. In the light of this discussion, we identify desirable features for fisheries simulation models aimed at policy evaluation, and particularly MPA evaluation.

Spatiotemporal variation in flow-dependent recruitment of long-lived riverine fish: Model development and evaluation

“…Spawning is a stochastic event and occurs only when the following ecological and physiological conditions are concurrently met: (1) water temperature ; (2) minimum discharge rate; and (3) the minimal GSI (Pelletier and Mahévas, 2005) (Appendix B).…”

Modelling marine protected areas: insights and hurdles

“…Selection of criteria for the appropriate model for a given problem is beyond the scope of this paper and has been tackled elsewhere in depth [54][55][56][57]. In brief, we concur that the nature of the question should dictate the type of model used.…”

Modelling the impacts of marine protected areas for mobile exploited fish populations and their fisheries: what we recently learnt and where we should be going

“…Nevertheless, complex spatially-and, eventually, seasonally-explicit models representing migrations between feeding and spawning areas and/or ontogenetic migrations and fishing fleet dynamics are also needed to provide detailed assessments for specific migratory populations and gain insights regarding the interaction between different fish movement types, fleet dynamics and the spatial distribution of MPAs. ISIS-Fish (Integration of Spatial Information for Simulation of Fisheries) is one such model (Pelletier and Mahévas 2005;Pelletier et al 2009). ISIS-Fish is a spatiallystructured, length-structured model, which relies on three interacting submodels pertaining, respectively, to fish population, exploitation, and management of multi-species multifleet (mixed) fisheries.…”

“…The probability of an individual hake migrating from one area to another during one of the ontogenetic migration events was based on rules that are a function of local bathymetry and alongshore direction. Hussein et al (2011) used the ISIS-FISH model (Pelletier and Mahévas 2005;Pelletier et al 2009) to assess the consequences of seasonal no-take targeted MPAs versus non-spatial management measures (fishing effort reduction, increases in gillnet mesh size) for the biomass and fisheries yields of the overexploited white seabream (Diplodus sargus sargus) population of the French Catalan coast. This application of ISIS-FISH has a monthly time step and analyses the conservation and fisheries effects of management measures after 20 years of simulation.…”

“…Moreover, biological MPA models often ignore fishers' movements other than fishing effort displacement, while fishers' behaviour has a considerable influence on yields (e.g., Kellner et al 2007;Botsford et al 2009;Grüss et al 2011a). Future applied biological modelling studies should systematically consider fishers' movement in response to spillover and other factors (e.g., travel costs) (Holland 2000;Pelletier and Mahévas 2005;Botsford et al 2009). …”